This disclosure relates generally to computer software and systems, particularly business application software and systems, and more particularly graphical user interfaces for the evaluation of preferences related to two-dimensional and three-dimensional images.
Product manufacturers operating globally utilize market research studies to obtain direct feedback about customer needs, values, and buying trends. For the purposes of such organizations, it is critical that these design considerations reflect the perspectives of all of a corporation's primary markets. Market research studies have taken several forms in an effort to identify product features that would be useful to and preferred by the widest customer population. For example, such studies have included focus groups, analysis of calls to customer service, interviews with industry experts, questionnaires/surveys, product testing, ethnographic techniques, among others. In one form, surveys containing images of proposed design concepts are presented to respondents in a hard copy format to solicit comments. Respondents comment on the various images by circling areas that they like or dislike as regarded such items as form factors or visual color changes and add written comments explaining their perspectives. This feedback is then collected, and the results are collated manually. Although much useful data may be gathered using this method, it presents several significant problems. The most serious include high analysis costs, difficulty in identifying meaningful patterns, limited survey distribution, and the extended amount of time necessary to complete the test itself.
Computer based survey tools have also been utilized to obtain customer data. Although computer surveys offered the benefits of electronic data collection and wider survey distribution, there was no means for respondents to physically draw and write on pages. Considering the visual and actual complexity of business products such as copiers, printers, and multi-function devices, useful design feedback and insights must necessarily be specific.
While these tools are useful, the product design process requires a high degree of specificity in obtaining actionable information relative to product appearance and architecture, and it is necessary that it include users world wide. The survey respondent needs the ability to identify specific areas of images and to provide comments relative to those areas. No existing survey applications permit respondents to draw on images to specify areas of interest and then comment on those areas. Nor are existing tools able to compile and analyze such data, in an accurate and easily comprehended manner.
To meet the needs of development of visually and operationally complex business products being marketed internationally, it would be desirable to have a market research tool that provides electronic distribution, worldwide participation, data security, ease of use, enabling of the positive or negative designation of any area of an image, enabling of association of specific comments to designated areas, quick, accurate, and cost effective analysis of the data, and visual presentation of the results in a clear, meaningful, and useful way.
All U.S. patents and published U.S. patent applications cited herein are fully incorporated by reference and are included only for purposes of adding alternative embodiments and are not intended to define or narrow the claim terms as set forth herein. The following patents or publications are noted.
U.S. Pat. No. 6,937,913 to Nishikawa et al. (“Product Design Process and Product Design Apparatus”) describes a product design process and apparatus for defining an optimal product concept capable of conveying customer satisfaction. The process includes analysis of wants and needs information, and, based on the analysis, weighting is carried out with respect to evaluation indices which have been previously stored in a storage device. The wants and needs information includes quantitative measures of the degree to which the user is likely to perceive a benefit latent in the product under consideration and inherent in the wants and needs information. An evaluation index is selected from among a plurality of weighted evaluation indices and a product design concept for which the primary evaluation index selected is a maximum or minimum is defined.
U.S. Pat. No. 7,016,882 to Afeyan et al. (“Method and Apparatus for Evolutionary Design”) describes generating and presenting, typically electronically, a number of design alternatives to persons who are participating in a design, selection, or market research exercise. The respondents transmit data indicative of their preferences among or between the presented design alternatives, and that data is used to derive a new generation of design alternatives or proposals. The new designs are generated through the use of a computer program exploiting a genetic or evolutionary computational technique. The process is repeated, typically for many iterations or cycles.
U.S. Published Patent Application No. 2005/0261953 to Malek et al. (“Determining Design Preferences of a Group”) teaches a method for generating and presenting, typically electronically, generations of design alternatives to persons participating in the design, selection, or market research exercise. The respondents transmit data indicative of their preferences among or between the presented design alternatives. Some of the data is used to conduct a conjoint analysis or non-convergent exercise to investigate the drivers of the preferences of the group or its members, and at least a portion are used to derive follow-on generations of design alternatives or proposals. The follow-on designs are preferably generated through the use of an evolutionary or genetic computer program, influenced by the respondents' preferences. The process results in the generation of one or more preferred product forms and information permitting a better understanding of what attributes of the product influence the preferences of the test group members.
U.S. Published Patent Application No. 2005/0261953 to Goldstein (“Computer System and Method for Development and Marketing of Consumer Products”) describes a computer-implemented method for the design and/or marketing of one or more consumer products based on an identified Icon includes capturing and storing in memory preferences of the Icon in accordance with at least one systematic survey of some of the preferences. One or more designs are created for a consumer product or for a space or scheme for a marketing promotion. The consumer product or space/scheme is stored in memory. The preferences may include aspects of a product or space and information regarding the background of the Icon.
The disclosed embodiments provide examples of improved solutions to the problems noted in the above Background discussion and the art cited therein. There is shown in these examples an improved method for operating a computer to analyze image evaluation data from electronic survey respondents to evaluate preferences related to two dimensional and three dimensional images. Data files, which include designated area data, image attributes, and survey respondent opinions for one or more images in an electronic survey, are received. A graphical user interface permits an operator to reformat the designated area data and set analysis parameters. Cluster analysis is performed on the data files to reduce the dimensionality of the designated area data and to classify areas of the survey images that generate positive and negative responses. The analysis produces coordinate data to map cluster classifications and for construction of a heat map. In association with descriptive statistical analysis, cluster score evaluation is performed to identify the clusters of interest. Respondent comments and results from the statistical analysis are linked to clusters of interest. The analysis results are saved for processing by a data viewing apparatus.
In an alternate embodiment there is disclosed a system for operating a computer to analyze image evaluation data from electronic survey respondents to evaluate preferences related to two dimensional and three dimensional images. The system provides a graphical user interface that enables an operator to reformat designated area data and set analysis parameters for received data files. The received data files include designated area data, image attributes, and survey respondent opinions for at least one image in an electronic survey. The system performs cluster analysis on the data files to reduce the dimensionality of the designated area data and to classify areas of the survey images that generate positive and negative responses. Coordinate data is produced to map cluster classifications onto the survey images and for construction of a heat map of the designated area data. Statistical analysis is performed on the data files and cluster score evaluation is performed to identify clusters of interest. The system links respondent comments and results from the statistical analysis to the clusters of interest and saves the results in a machine readable file.
In yet another embodiment there is disclosed a computer-readable storage medium having computer readable program code embodied in the medium which, when the program code is executed by a computer, causes the computer to perform method steps for operating a computer to analyze image evaluation data from electronic survey respondents to evaluate preferences related to two dimensional and three dimensional images. Data files, which include designated area data, image attributes, and survey respondent opinions for one or more images in an electronic survey, are received. A graphical user interface permits an operator to reformat the designated area data and set analysis parameters. Cluster analysis is performed on the data files to reduce the dimensionality of the designated area data and to classify areas of the survey images that generate positive and negative responses. The analysis produces coordinate data to map cluster classifications and for construction of a heat map. In association with descriptive statistical analysis, cluster score evaluation is performed to identify the clusters of interest. Respondent comments and results from the statistical analysis are linked to clusters of interest. The analysis results are saved for processing by a data viewing apparatus.